%A A. Ruszczynski
%T On Augmented Lagrangian Decomposition Methods For Multistage Stochastic Programs
%X A general decomposition framework for large convex optimization problems based on augmented Lagrangians is described. The approach is then applied to multistage stochastic programming problems in two different ways: by decomposing the problem into scenarios or decomposing it into nodes  corresponding to stages. In both cases the method has favorable convergence  properties and a structure which makes it convenient for parallel computing  environments.
%C IIASA, Laxenburg, Austria
%D 1994
%I WP-94-005
%L iiasa4204